Anni Salminen, Patrik Sioris, Juha Jernman, Nele Veide, Anton Kontunen, Meri Mäkelä, Markus Karjalainen, Minna Kelloniemi, Niku Oksala, Antti Roine
{"title":"从手术烟雾中检测磷脂可区分基底细胞癌：一项原理证明研究","authors":"Anni Salminen, Patrik Sioris, Juha Jernman, Nele Veide, Anton Kontunen, Meri Mäkelä, Markus Karjalainen, Minna Kelloniemi, Niku Oksala, Antti Roine","doi":"10.1155/dth/6179799","DOIUrl":null,"url":null,"abstract":"<div>\n <p><b>Background:</b> Basal cell carcinoma (BCC) is a nonmelanocytic skin cancer and the most common malignancy in Caucasians. Diagnostics and treatment of BCC cause significant health-related stress for many patients and costs for public health care systems. Differential mobility spectrometry (DMS) is a sensitive method for detection of gaseous molecules. The DMS-derived automatic tissue analysis system (ATAS) utilises diathermy-generated surgical smoke to distinguish cancerous tissue from normal tissue based on lipid profiling between the tissues.</p>\n <p><b>Objectives:</b> The aim of this study was to create a surrogate porcine model to test the feasibility of the ATAS in lipid detection of skin. Another objective was to determine whether BCC of human skin could be identified from healthy skin using lipid profiling.</p>\n <p><b>Methods:</b> Porcine ear skin was used to establish a three-group porcine model for lipid profile detection. Lecithin was chosen as a marker to demonstrate elevated phospholipid levels in one of the groups. We also recruited five BCC patients to collect BCC tumour biopsies and healthy skin biopsies to test the model in human samples. In both models, all samples were processed with the ATAS to test the accuracy of lipid profiling and resolution between the groups.</p>\n <p><b>Results:</b> In the porcine model<span>,</span> the classification accuracy was 74.5% for three groups (unprocessed porcine skin, fine-grained porcine skin, and lecithin-marked fine-grained porcine skin) and 91.8% for two groups (unprocessed porcine skin and fine-grained porcine skin combined into one group in comparison to lecithin-marked fine-grained porcine skin). The support vector machine (SVM) classifier model trained on porcine surrogate samples was then used to analyse a small number of human BCC and healthy skin samples with 95% accuracy.</p>\n <p><b>Conclusion:</b> DMS-based differentiation of porcine skin samples based on surgical smoke is possible. This study is a step towards a method to distinguish human BCC from healthy skin from surgical smoke by the ATAS. The presented skin identification of DMS analysis of surgical smoke opens the possibility to research the method in a larger sample number of human BCC and healthy skin samples as well as develop the method and ATAS towards a clinical tool for margin assessment.</p>\n </div>","PeriodicalId":11045,"journal":{"name":"Dermatologic Therapy","volume":"2025 1","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/dth/6179799","citationCount":"0","resultStr":"{\"title\":\"Phospholipid Detection From Surgical Smoke Distinguishes Basal Cell Carcinoma: A Proof-of-Principle Study\",\"authors\":\"Anni Salminen, Patrik Sioris, Juha Jernman, Nele Veide, Anton Kontunen, Meri Mäkelä, Markus Karjalainen, Minna Kelloniemi, Niku Oksala, Antti Roine\",\"doi\":\"10.1155/dth/6179799\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n <p><b>Background:</b> Basal cell carcinoma (BCC) is a nonmelanocytic skin cancer and the most common malignancy in Caucasians. Diagnostics and treatment of BCC cause significant health-related stress for many patients and costs for public health care systems. Differential mobility spectrometry (DMS) is a sensitive method for detection of gaseous molecules. The DMS-derived automatic tissue analysis system (ATAS) utilises diathermy-generated surgical smoke to distinguish cancerous tissue from normal tissue based on lipid profiling between the tissues.</p>\\n <p><b>Objectives:</b> The aim of this study was to create a surrogate porcine model to test the feasibility of the ATAS in lipid detection of skin. Another objective was to determine whether BCC of human skin could be identified from healthy skin using lipid profiling.</p>\\n <p><b>Methods:</b> Porcine ear skin was used to establish a three-group porcine model for lipid profile detection. Lecithin was chosen as a marker to demonstrate elevated phospholipid levels in one of the groups. We also recruited five BCC patients to collect BCC tumour biopsies and healthy skin biopsies to test the model in human samples. In both models, all samples were processed with the ATAS to test the accuracy of lipid profiling and resolution between the groups.</p>\\n <p><b>Results:</b> In the porcine model<span>,</span> the classification accuracy was 74.5% for three groups (unprocessed porcine skin, fine-grained porcine skin, and lecithin-marked fine-grained porcine skin) and 91.8% for two groups (unprocessed porcine skin and fine-grained porcine skin combined into one group in comparison to lecithin-marked fine-grained porcine skin). The support vector machine (SVM) classifier model trained on porcine surrogate samples was then used to analyse a small number of human BCC and healthy skin samples with 95% accuracy.</p>\\n <p><b>Conclusion:</b> DMS-based differentiation of porcine skin samples based on surgical smoke is possible. This study is a step towards a method to distinguish human BCC from healthy skin from surgical smoke by the ATAS. The presented skin identification of DMS analysis of surgical smoke opens the possibility to research the method in a larger sample number of human BCC and healthy skin samples as well as develop the method and ATAS towards a clinical tool for margin assessment.</p>\\n </div>\",\"PeriodicalId\":11045,\"journal\":{\"name\":\"Dermatologic Therapy\",\"volume\":\"2025 1\",\"pages\":\"\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2025-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1155/dth/6179799\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Dermatologic Therapy\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1155/dth/6179799\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"DERMATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Dermatologic Therapy","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/dth/6179799","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"DERMATOLOGY","Score":null,"Total":0}
Phospholipid Detection From Surgical Smoke Distinguishes Basal Cell Carcinoma: A Proof-of-Principle Study
Background: Basal cell carcinoma (BCC) is a nonmelanocytic skin cancer and the most common malignancy in Caucasians. Diagnostics and treatment of BCC cause significant health-related stress for many patients and costs for public health care systems. Differential mobility spectrometry (DMS) is a sensitive method for detection of gaseous molecules. The DMS-derived automatic tissue analysis system (ATAS) utilises diathermy-generated surgical smoke to distinguish cancerous tissue from normal tissue based on lipid profiling between the tissues.
Objectives: The aim of this study was to create a surrogate porcine model to test the feasibility of the ATAS in lipid detection of skin. Another objective was to determine whether BCC of human skin could be identified from healthy skin using lipid profiling.
Methods: Porcine ear skin was used to establish a three-group porcine model for lipid profile detection. Lecithin was chosen as a marker to demonstrate elevated phospholipid levels in one of the groups. We also recruited five BCC patients to collect BCC tumour biopsies and healthy skin biopsies to test the model in human samples. In both models, all samples were processed with the ATAS to test the accuracy of lipid profiling and resolution between the groups.
Results: In the porcine model, the classification accuracy was 74.5% for three groups (unprocessed porcine skin, fine-grained porcine skin, and lecithin-marked fine-grained porcine skin) and 91.8% for two groups (unprocessed porcine skin and fine-grained porcine skin combined into one group in comparison to lecithin-marked fine-grained porcine skin). The support vector machine (SVM) classifier model trained on porcine surrogate samples was then used to analyse a small number of human BCC and healthy skin samples with 95% accuracy.
Conclusion: DMS-based differentiation of porcine skin samples based on surgical smoke is possible. This study is a step towards a method to distinguish human BCC from healthy skin from surgical smoke by the ATAS. The presented skin identification of DMS analysis of surgical smoke opens the possibility to research the method in a larger sample number of human BCC and healthy skin samples as well as develop the method and ATAS towards a clinical tool for margin assessment.
期刊介绍：
Dermatologic Therapy has been created to fill an important void in the dermatologic literature: the lack of a readily available source of up-to-date information on the treatment of specific cutaneous diseases and the practical application of specific treatment modalities. Each issue of the journal consists of a series of scholarly review articles written by leaders in dermatology in which they describe, in very specific terms, how they treat particular cutaneous diseases and how they use specific therapeutic agents. The information contained in each issue is so practical and detailed that the reader should be able to directly apply various treatment approaches to daily clinical situations. Because of the specific and practical nature of this publication, Dermatologic Therapy not only serves as a readily available resource for the day-to-day treatment of patients, but also as an evolving therapeutic textbook for the treatment of dermatologic diseases.
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